FORMATION OF A DATASET OF CRYPTOGRAPHIC ALGORITHMS FOR ENSURING DATA CONFIDENTIALITY TRANSFERRED FROM RECONNAISSANCE AND SEARCH UAV
DOI:
https://doi.org/10.28925/2663-4023.2023.20.205219Abstract
The rapid development of unmanned aerial vehicles (UAV) has significantly changed the conduct of military operations and warfare strategies, offering numerous advantages in terms of intelligence, surveillance and combat capabilities. The use of UAV in the military sphere provides more complete situational awareness, operational efficiency and reduces risks to personnel. In addition, in the field of intelligence and surveillance, UAV have revolutionized the context of intelligence gathering. Equipped with the latest image processing systems, sensors and high-resolution cameras, they can conduct real-time aerial photography, monitor enemy activity and gather critical intelligence without putting the military at risk. UAV make it possible to conduct long-term operations in conditions of secrecy, providing commanders with valuable information for making strategic decisions. However, the issue of ensuring the confidentiality of critical data collected using UAV remains unresolved. With this in mind, in this paper universal dataset of cryptographic algorithms was created, it uses a neural network to select the optimal encryption algorithm. To form such a dataset, it was necessary to evaluate the speed of the crypto algorithms, their cryptographic security and other parameters. The developed dataset in synthesis with a neural network can be used to select the optimal crypto algorithm depending on the operating conditions. In further research, the authors plan to determine the criteria for using the generated dataset by neural networks and develop a knowledge base for neural network training.
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